Lane departure warning method based on Hough transform

A lane departure warning and Hough transform technology, applied in the field of computer vision, can solve problems such as reducing the accuracy of the system, affecting the accuracy of the system, and detecting errors.

Active Publication Date: 2018-10-12
SOUTH CHINA UNIV OF TECH +1
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AI Technical Summary

Problems solved by technology

If there are interference objects or blurred lane lines, it may lead to detection errors, greatly reducing the accuracy of the

Method used

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  • Lane departure warning method based on Hough transform
  • Lane departure warning method based on Hough transform
  • Lane departure warning method based on Hough transform

Examples

Experimental program
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Effect test

Embodiment

[0056] refer to figure 1 , the lane departure warning method based on Hough transform proposed by the present invention comprises the following steps:

[0057] S1. Collect a video image through a camera, and segment a region of interest (hereinafter referred to as ROI region). Delineate the lower half of the image as the region of interest to reduce the impact of irrelevant regions on the algorithm.

[0058] S2, process the image frame collected, convert the RGB color image into a grayscale image, the result is as follows figure 2 As shown, the calculation formula is as follows:

[0059] I(u,v)=0.299*I R (u,v)+0.587*I G (u,v)+0.114*I B (u,v)

[0060] Intercept the grayscale image of the region of interest, the result is as follows image 3 shown. Use the improved one-way gradient operator to detect the edge of the lane line, and the calculation formula is as follows:

[0061] f(u , v)=2×I(u , v)-I(u+S,v)-I(u-S,v)-|I(u+S,v)-I(u-S,v)|

[0062] Wherein, the parameter...

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Abstract

The invention discloses a lane departure warning method based on Hough transform. The method comprises the steps of carrying out region of interest segmentation on an image; graying region of interestimages; carrying out edge detection on the grayed images through utilization of an improved unidirectional gradient operator, thereby obtaining edge images; carrying out binarization processing on the images through utilization of an otsu algorithm; obtaining a candidate straight line set through Hough transform, dividing the candidate straight line set into a left lane straight line set and a right lane straight line set according to slopes, screening the two straight line sets through combination of vanishing point constraint and a random sample consistency algorithm, thereby obtaining optimum left and right lane line parameters; establishing two Kalman filters to track left and right optimum lane lines; and estimating relative lateral offset and a change trend through utilization of the left and right lane line slopes, identifying lane departure and carrying out warning. According to the method, the lane departure problem in driving can be effectively identified, and the robustnessand timeliness of the a lane departure warning system are improved.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a lane departure warning method based on Hough transform. Background technique [0002] Along with the continuous development of society and the continuous improvement of the national economy, the number of cars is increasing day by day. Due to the large population base in our country, the sharp increase in the number of cars has led to a high incidence of traffic accidents, which has caused huge losses to the national economy and even threatened personal safety. According to the results of relevant investigations, the causes of traffic accidents are rarely caused by bad weather and the road itself, and more are caused by the driver's own problems, and lane departure is one of the main reasons. [0003] Most of the current lane departure warning systems are developed based on computer vision technology, and generally can only play an effective role on roads with clear la...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/588
Inventor 林耀荣赵雪灿张巧灵
Owner SOUTH CHINA UNIV OF TECH
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